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Katherine Foag

Katie joined Allina Health in July 2013 as a Data Analyst and is happy to now be a part of the Health Catalyst team. Prior to coming to Allina, she completed a Masters in Public Health at the University of Minnesota. Meanwhile, she supported development of a youth violence prevention program at the Minneapolis Health Department and worked with the Minnesota Organization on Fetal Alcohol Syndrome to coordinate inter-agency partnerships.

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Katherine Foag
Taylor Larsen

Top Five Elements of an Effective Readmission Risk Score

Under value-based healthcare and the 2012 Hospital Readmission Reduction Program, healthcare organizations are more motivated than ever to reduce their incidence of preventable readmissions.
Health systems can reduce risk of hospital readmissions by developing readmission risk scores tailored specifically to their populations. A risk model that meets the following five requirements will have significant predictive value and is most likely to achieve systemwide adoption:

Identifies at-risk patients early.
Separates patients relevant to the disease-specific identification method and intervention strategy from all other in-hospital patients.
Uses organization-specific data to train a disease-specific model.
Exceeds performance of existing models.
Is developed in collaboration with domain experts.

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